Learning in the Early Years: A Multimodal Perspective

Date:

27/11/2014

Organised by:

London Knowledge Lab, Institute of Education

Presenter:

Diane Mavers

Level:

Intermediate (some prior knowledge)

Contact:

Naomi Buneman mode@ioe.ac.uk 020 7763 2199

Map:

View in Google Maps  (WC1N 3QS)

Venue:

To be confirmed

Description:

This seminar investigates how a multimodal perspective can provide insights into learning in the early years. Young children are surrounded by, engage with, interpret and express meanings communicated in a huge variety of ways. As they interact with others, explore everyday objects and play, meanings are made, for example, in looking, running, holding, making graphic marks, acting out, and so on, as well as speech. Based on research video data gathered in the nursery, the Reception class and the home, we will explore how a multimodal approach to qualitative analysis can inform our interpretation and understanding of early learning. Opportunities for debate encourage participants to reflect on associated issues and to contribute their own interests and concerns.

 

Programme

10.30-10.40 Welcome

10.40-11.25 Introduction (Diane Mavers)

11.25-11.45 COFFEE

11.45-12.15 Discussion: multimodality and early learning in participants’own research

12.15-13.00 Young children as apprentice story writers (Rosie Flewitt, in collaboration with Teresa Cremin)

13.00-13.45 LUNCH

13.45-14:30 Recording learning in young children’s play (Kate Cowan)

14.30-14.45 TEA

14.45-15.30: Literacy learning in early childhood (Lesley Lancaster)

15.30-16.00: Closing plenary

Cost:

Fees: PhD students: £30 Staff at UK academic institutions, RCUK funded researchers, public sector staff and staff at registered charity organizations: £60

Website and registration:

Region:

Greater London

Keywords:

Visual Methods, Qualitative Data Handling and Data Analysis, Visual Data Analysis, Early Years , Multimodal

Related publications and presentations:

Visual Methods
Qualitative Data Handling and Data Analysis
Visual Data Analysis

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